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      칼라영상을 이용한 방울토마토 품질 인자 계측에 관한 연구 = Study on Quality Factor Measurement for Cherry Tomato using Color Imagery

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      https://www.riss.kr/link?id=A105056009

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      다국어 초록 (Multilingual Abstract)

      Surface color is the most important quality factor for the grade evaluation of cherry tomato. Color is one of the representative indicators for the maturity which is closely related to the internal quality of cherry tomato, such as firmness, sugar content, and acidity. This study was carried out to investigate the relationship between surface color and internal quality of cherry tomatoes harvested from both hydroponic and soil culture at different ripening stages. To calculate the color values of cherry tomatoes an automatic color imaging system was constructed. A specially designed image processing algorithm for the color measurement was developed. The color values of L*, a*, b* were calculated from the initial color values of RGB and then compared with the internal quality. Statistical analyses indicated that the internal quality was more highly correlated with the surface color than size of cherry tomatoes. Color image features were also investigated to detect external damage of cherry tomatoes. The value of (R value - R mean value)/R mean value was the most effective image feature for the detection of damaged areas on the surface of cherry tomatoes. The results of this study demonstrated the feasibility of color sorting process as an alternative of the conventional drum type size sorting system for cherry tomato industry.
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      Surface color is the most important quality factor for the grade evaluation of cherry tomato. Color is one of the representative indicators for the maturity which is closely related to the internal quality of cherry tomato, such as firmness, sugar con...

      Surface color is the most important quality factor for the grade evaluation of cherry tomato. Color is one of the representative indicators for the maturity which is closely related to the internal quality of cherry tomato, such as firmness, sugar content, and acidity. This study was carried out to investigate the relationship between surface color and internal quality of cherry tomatoes harvested from both hydroponic and soil culture at different ripening stages. To calculate the color values of cherry tomatoes an automatic color imaging system was constructed. A specially designed image processing algorithm for the color measurement was developed. The color values of L*, a*, b* were calculated from the initial color values of RGB and then compared with the internal quality. Statistical analyses indicated that the internal quality was more highly correlated with the surface color than size of cherry tomatoes. Color image features were also investigated to detect external damage of cherry tomatoes. The value of (R value - R mean value)/R mean value was the most effective image feature for the detection of damaged areas on the surface of cherry tomatoes. The results of this study demonstrated the feasibility of color sorting process as an alternative of the conventional drum type size sorting system for cherry tomato industry.

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      참고문헌 (Reference)

      1 박우포, "포장 조건에 따른 방울토마토의 저장 중 품질 특성 변화" 한국식품저장유통학회 9 (9): 121-125, 2002

      2 최규홍, "토마토 자동 선별시스템 개발" 4 (4): 282-289, 1999

      3 김대용, "착색도를 이용한 방울토마토 품질측정에 관한 연구" 14 (14): 383-386, 2009

      4 USDA, "United states standards for grades of fresh tomatoes" United States Department of Agriculture, Agricultural Marketing Service 1997

      5 Polder, G., "Tomato sorting using independent component analysis on spectral images" 9 (9): 253-259, 2003

      6 Choi, K., "Tomato maturity evaluation using color image analysis" 38 (38): 171-176, 1995

      7 Pedro, A.M.K., "Simultaneously calibrating solids, sugars and acidity of tomato products using PLS2 and NIR spectroscopy" 595 (595): 221-227, 2007

      8 Clement, A., "Nondestructive Measurement of Fresh Tomato Lycopene Content and Other Physicochemical Characteristics Using Visible-NIR Spectroscopy" 56 (56): 9813-9818, 2008

      9 Jahns, G., "Measuring image analysis attributes and modelling fuzzy consumer aspects for tomato quality grading" 31 (31): 17-29, 2001

      10 Laykin, S., "Image-processing algorithms for tomato classification" 45 (45): 851-858, 2002

      1 박우포, "포장 조건에 따른 방울토마토의 저장 중 품질 특성 변화" 한국식품저장유통학회 9 (9): 121-125, 2002

      2 최규홍, "토마토 자동 선별시스템 개발" 4 (4): 282-289, 1999

      3 김대용, "착색도를 이용한 방울토마토 품질측정에 관한 연구" 14 (14): 383-386, 2009

      4 USDA, "United states standards for grades of fresh tomatoes" United States Department of Agriculture, Agricultural Marketing Service 1997

      5 Polder, G., "Tomato sorting using independent component analysis on spectral images" 9 (9): 253-259, 2003

      6 Choi, K., "Tomato maturity evaluation using color image analysis" 38 (38): 171-176, 1995

      7 Pedro, A.M.K., "Simultaneously calibrating solids, sugars and acidity of tomato products using PLS2 and NIR spectroscopy" 595 (595): 221-227, 2007

      8 Clement, A., "Nondestructive Measurement of Fresh Tomato Lycopene Content and Other Physicochemical Characteristics Using Visible-NIR Spectroscopy" 56 (56): 9813-9818, 2008

      9 Jahns, G., "Measuring image analysis attributes and modelling fuzzy consumer aspects for tomato quality grading" 31 (31): 17-29, 2001

      10 Laykin, S., "Image-processing algorithms for tomato classification" 45 (45): 851-858, 2002

      11 Flores, K., "Feasibility in NIRS instruments for predicting internal quality in intact tomato" 91 (91): 311-318, 2009

      12 Lana, M.M., "Effects of storage temperature and stage of ripening on RGB colour aspects of fresh-cut tomato pericarp using video image analysis" 17 (17): 871-879, 2006

      13 Baranska, M., "Determination of lycopene and beta-carotene content in tomato fruits and related products: Comparison of FT-Raman, ATRIR, and NIR spectroscopy" 78 (78): 8456-8461, 2006

      14 Batu, A., "Determination of acceptable firmness and colour values of tomatoes" 61 (61): 471-475, 2004

      15 Lana, M.M., "Assessment of changes in optical properties of fresh-cut tomato using video image analysis" 41 (41): 296-306, 2006

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      학술지 이력

      학술지 이력
      연월일 이력구분 이력상세 등재구분
      2026 평가예정 재인증평가 신청대상 (재인증)
      2020-01-01 평가 등재학술지 유지 (재인증) KCI등재
      2017-01-01 평가 등재학술지 선정 (계속평가) KCI등재
      2016-03-31 학술지명변경 한글명 : 농업과학연구 -> Korean Journal of Agricultural Science
      외국어명 : JOURNAL OF AGRICULTURAL SCIENCE -> Korean Journal of Agricultural Science
      KCI등재후보
      2015-01-01 평가 등재후보학술지 선정 (신규평가) KCI등재후보
      2013-04-01 평가 등재후보 탈락 (기타)
      2011-01-01 평가 등재후보 1차 FAIL (등재후보1차) KCI등재후보
      2009-01-01 평가 등재후보학술지 선정 (신규평가) KCI등재후보
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      학술지 인용정보

      학술지 인용정보
      기준연도 WOS-KCI 통합IF(2년) KCIF(2년) KCIF(3년)
      2016 0.28 0.28 0
      KCIF(4년) KCIF(5년) 중심성지수(3년) 즉시성지수
      0 0 0 0.1
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